Prompt A Structured Q&A Response Using LeMUR

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import assemblyai as aai
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import xml.etree.ElementTree as ET
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aai.settings.api_key = "YOUR_API_KEY"
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audio_url = "https://storage.googleapis.com/aai-web-samples/meeting.mp4"
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transcript = aai.Transcriber().transcribe(audio_url)
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def construct_question(question):
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    question_str = f"Question: {question.question}"
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    if question.context:
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        question_str += f"\nContext: {question.context}"
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    # Set default answer_format to "short sentence" if not provided
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    if not question.answer_format:
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        question.answer_format = "short sentence"
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    question_str += f"\nAnswer Format: {question.answer_format}"
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    if question.answer_options:
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        options_str = ", ".join(question.answer_options)
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        question_str += f"\nOptions: {options_str}"
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    return question_str + "\n"
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def escape_xml_characters(xml_string):
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    return xml_string.replace('&', '&')
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questions = [
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    aai.LemurQuestion(
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        question="What are the top level KPIs for engineering?",
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        context="KPI stands for key performance indicator",
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        answer_format="short sentence"),
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    aai.LemurQuestion(
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        question="How many days has it been since the data team has gotten updated metrics?",
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        answer_options=["1", "2", "3", "4", "5", "6", "7", "more than 7"]),
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    aai.LemurQuestion(
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        question="What are the future plans for the project?")
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]
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question_str = '\n'.join(construct_question(q) for q in questions)
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prompt = f"""You are an expert at giving accurate answers to questions about texts.
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  No preamble.
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  Given the series of questions, answer the questions.
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  Each question may follow up with answer format, answer options, and context for each question.
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  It is critical that you follow the answer format and answer options for each question.
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  When context is provided with a question, refer to it when answering the question.
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  You are useful, true and concise, and write in perfect English.
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  Only the question is allowed between the <question> tag. Do not include the answer format, options, or question context in your response.
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  Only text is allowed between the <question> and <answer> tags.
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  XML tags are not allowed between the <question> and <answer> tags.
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  End your response with a closing </response> tag.
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  For each question-answer pair, format your response according to the template provided below:
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Template for response:
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<responses>
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  <response>
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    <question>The question</question>
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    <answer>Your answer</answer>
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  </response>
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  <response>
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    ...
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  </response>
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  ...
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</responses>
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These are the questions:
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{question_str}
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"""
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result = transcript.lemur.task(
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    prompt,
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    final_model=aai.LemurModel.claude3_5_sonnet
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)
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response = result.response
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# Escape special XML characters and strip any leading/trailing whitespace
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clean_response = escape_xml_characters(response).strip()
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root = ET.fromstring(clean_response)
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for response in root.findall('response'):
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    question = response.find('question').text
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    answer = response.find('answer').text
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    print(f"Question: {question}")
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    print(f"Answer: {answer}")

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import assemblyai as aai
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aai.settings.api_key = "API_KEY_HERE"

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audio_url = "https://storage.googleapis.com/aai-web-samples/meeting.mp4"
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transcript = aai.Transcriber().transcribe(audio_url)

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def construct_question(question):
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    question_str = f"Question: {question.question}"
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    if question.context:
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        question_str += f"\nContext: {question.context}"
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    # Set default answer_format to "short sentence" if not provided
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    if not question.answer_format:
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        question.answer_format = "short sentence"
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    question_str += f"\nAnswer Format: {question.answer_format}"
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    if question.answer_options:
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        options_str = ", ".join(question.answer_options)
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        question_str += f"\nOptions: {options_str}"
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    return question_str + "\n"

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questions = [
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    aai.LemurQuestion(
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        question="What are the top level KPIs for engineering?",
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        context="KPI stands for key performance indicator",
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        answer_format="short sentence"),
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    aai.LemurQuestion(
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        question="How many days has it been since the data team has gotten updated metrics?",
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        answer_options=["1", "2", "3", "4", "5", "6", "7", "more than 7"]),
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    aai.LemurQuestion(
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        question="What are the future plans for the project?")
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]

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question_str = '\n'.join(construct_question(q) for q in questions)

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prompt = f"""You are an expert at giving accurate answers to questions about texts.
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  No preamble.
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  Given the series of questions, answer the questions.
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  Each question may follow up with answer format, answer options, and context for each question.
5
  It is critical that you follow the answer format and answer options for each question.
6
  When context is provided with a question, refer to it when answering the question.
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  You are useful, true and concise, and write in perfect English.
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  Only the question is allowed between the <question> tag. Do not include the answer format, options, or question context in your response.
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  Only text is allowed between the <question> and <answer> tags.
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  XML tags are not allowed between the <question> and <answer> tags.
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  End your response with a closing </response> tag.
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  For each question-answer pair, format your response according to the template provided below:
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Template for response:
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<responses>
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  <response>
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    <question>The question</question>
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    <answer>Your answer</answer>
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  </response>
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  <response>
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    ...
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  </response>
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  ...
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</responses>
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These are the questions:
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{question_str}
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"""

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result = transcript.lemur.task(
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    prompt,
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    final_model=aai.LemurModel.claude3_5_sonnet
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)
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response = result.response
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print(response)

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import xml.etree.ElementTree as ET
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def escape_xml_characters(xml_string):
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    return xml_string.replace('&', '&')
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# Escape special XML characters and strip any leading/trailing whitespace
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clean_response = escape_xml_characters(response).strip()
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root = ET.fromstring(clean_response)
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for response in root.findall('response'):
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    question = response.find('question').text
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    answer = response.find('answer').text
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    print(f"Question: {question}")
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    print(f"Answer: {answer}")